Predictors of Problematic Social Media Use in a Nationally Representative Sample of Adolescents in Luxembourg
Bibliographic Data
| ID | 15510453 |
|---|---|
| Authors | Claire van Duin (University of Luxembourg, corresponding author), Andreas Heinz (0000-0001-5405-9065, University of Luxembourg), Helmut Willems (University of Luxembourg) |
| Year | 2021 |
| Volume | 18 |
| Issue | 22 |
| Pages | 11878-11878 |
| Publication date | 2021-11-12 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph182211878 |
| PMID | 34831633 |
| OpenAlex | W3213912786 |
| Language | EN |
| Citations received | 10 |
| References cited | 50 |
Social media use has increased substantially over the past decades, especially among adolescents. A proportion of adolescents develop a pattern of problematic social media use (PSMU). Predictors of PSMU are insufficiently understood and researched. This study aims to investigate predictors of PSMU in a nationally representative sample of adolescents in Luxembourg. Data from the Health Behavior in School-aged Children (HBSC) study in Luxembourg were used, in which 8687 students aged 11-18 years old participated. The data were analyzed using hierarchical multiple regression. A range of sociodemographic, social support, well-being and media use predictors were added to the model in four blocks. The predictors in the final model explained 22.3% of the variance in PSMU. The block of sociodemographic predictors explained the lowest proportion of variance in PSMU compared with the other blocks. Age negatively predicted PSMU. Of the predictors related to social support, cyberbullying perpetration was the strongest predictor of PSMU. Perceived stress and psychosomatic complaints positively predicted PSMU. The intensity of electronic media communication and preference for online social interaction were stronger predictors of PSMU than the other predictors in the model. The results indicate that prevention efforts need to consider the diverse range of predictors related to PSMU
Explained variation · Multilevel model · Regression analysis · Social media · Social support · Statistics · Variance (accounting · Child Development and Digital Technology · Clinical Psychology · Demography · Impact of Technology on Adolescents · Psychology · Social Media and Politics · Social Psychology
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| Citations per year | 2.5 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |